Proteome Analysis of Sorangium cellulosum Employing 2D-HPLC-MS/MS and Improved Database Searching Strategies for CID and ETD Fragment Spectra

Myxobacterial Genomics and Post-Genomics: A Review of Genome Biology, Genome Sequences and Related 'Omics Studies

Myxobacteria are fascinating and complex microbes. They prey upon other members of the soil microbiome by secreting antimicrobial proteins and metabolites, and will undergo multicellular development if starved. The genome sequence of the model myxobacterium Myxococcus xanthus DK1622 was published in 2006 and 15 years later, 163 myxobacterial genome sequences have now been made public. This explosion in genomic data has enabled comparative genomics analyses to be performed across the taxon, providing important insights into myxobacterial gene conservation and evolution. The availability of myxobacterial genome sequences has allowed system-wide functional genomic investigations into entire classes of genes. It has also enabled post-genomic technologies to be applied to myxobacteria, including transcriptome analyses (microarrays and RNA-seq), proteome studies (gel-based and gel-free), investigations into protein–DNA interactions (ChIP-seq) and metabolism. Here, we review myxobacterial genome sequencing, and summarise the insights into myxobacterial biology that have emerged as a result. We also outline the application of functional genomics and post-genomic approaches in myxobacterial research, highlighting important findings to emerge from seminal studies. The review also provides a comprehensive guide to the genomic datasets available in mid-2021 for myxobacteria (including 24 genomes that we have sequenced and which are described here for the first time).

Identification of novel PAMP-triggered phosphorylation and dephosphorylation events in Arabidopsis thaliana by quantitative phosphoproteomic analysis

Signaling cascades rely strongly on protein kinase-mediated substrate phosphorylation. Currently a major challenge in signal transduction research is to obtain high confidence substrate phosphorylation sites and assign them to specific kinases. In response to bacterial flagellin, a pathogen-associated molecular pattern (PAMP), we searched for rapidly phosphorylated proteins in Arabidopsis thaliana by combining multistage activation (MSA) and electron transfer dissociation (ETD) fragmentation modes, which generate complementary spectra and identify phosphopeptide sites with increased reliability. Of a total of 825 phosphopeptides, we identified 58 to be differentially phosphorylated. These peptides harbor kinase motifs of mitogen-activated protein kinases (MAPKs) and calcium-dependent protein kinases (CDPKs), as well as yet unknown protein kinases. Importantly, 12 of the phosphopeptides show reduced phosphorylation upon flagellin treatment. Since protein abundance levels did not change, these results indicate that flagellin induces not only various protein kinases but also protein phosphatases, even though a scenario of inhibited kinase activity may also be possible.

Electron transfer dissociation mass spectrometry in proteomics

Mass spectrometry has rapidly evolved to become the platform of choice for proteomic analysis. While CID remains the major fragmentation method for peptide sequencing, electron transfer dissociation (ETD) is emerging as a complementary method for the characterization of peptides and post-translational modifications (PTMs). Here, we review the evolution of ETD and some of its newer applications including characterization of PTMs, non-tryptic peptides and intact proteins. We will also discuss some of the unique features of ETD such as its complementarity with CID and the use of alternating CID/ETD along with issues pertaining to analysis of ETD data. The potential of ETD for applications such as multiple reaction monitoring and proteogenomics in the future will also be discussed.

Improved peptide identification for proteomic analysis based on comprehensive characterization of electron transfer dissociation spectra

In recent years, electron transfer dissociation (ETD) has enjoyed widespread applications from sequencing of peptides with or without post-translational modifications to top-down analysis of intact proteins. However, peptide identification rates from ETD spectra compare poorly with those from collision induced dissociation (CID) spectra, especially for doubly charged precursors. This is in part due to an insufficient understanding of the characteristics of ETD and consequently a failure of database search engines to make use of the rich information contained in the ETD spectra. In this study, we statistically characterized ETD fragmentation patterns from a collection of 461 440 spectra and subsequently implemented our findings into pFind, a database search engine developed earlier for CID data. From ETD spectra of doubly charged precursors, pFind 2.1 identified 63-122% more unique peptides than Mascot 2.2 under the same 1% false discovery rate. For higher charged peptides as well as phosphopeptides, pFind 2.1 also consistently obtained more identifications. Of the features built into pFind 2.1, the following two greatly enhanced its performance: (1) refined automatic detection and removal of high-intensity peaks belonging to the precursor, charge-reduced precursor, or related neutral loss species, whose presence often set spectral matching askew; (2) a thorough consideration of hydrogen-rearranged fragment ions such as z + H and c - H for peptide precursors of different charge states. Our study has revealed that different charge states of precursors result in different hydrogen rearrangement patterns. For a fragment ion, its propensity of gaining or losing a hydrogen depends on (1) the ion type (c or z) and (2) the size of the fragment relative to the precursor, and both dependencies are affected by (3) the charge state of the precursor. In addition, we discovered ETD characteristics that are unique for certain types of amino acids (AAs), such as a prominent neutral loss of SCH(2)CONH(2) (90.0014 Da) from z ions with a carbamidomethylated cysteine at the N-terminus and a neutral loss of histidine side chain C(4)N(2)H(5) (81.0453 Da) from precursor ions containing histidine. The comprehensive list of ETD characteristics summarized in this paper should be valuable for automated database search, de novo peptide sequencing, and manual spectral validation.

A novel mass spectrometry cluster for high-throughput quantitative proteomics

We have developed and implemented a novel mass spectrometry (MS) platform combining the advantages of high mass accuracy and resolving power of Fourier transform ion cyclotron resonance (FTICR) with the economy and speed of multiple ion traps for tandem mass spectrometry. The instruments are integrated using novel algorithms and software and work in concert as one system. Using chromatographic time compression, a single expensive FTICR mass spectrometer can match the throughput of multiple relatively inexpensive ion trap instruments. Liquid chromatography (LC)-mass spectrometry data from the two types of spectrometers are aligned and combined to hybrid datasets, from which peptides are identified using accurate mass from the FTICR data and tandem mass spectra from the ion trap data. In addition, the high resolving power and dynamic range of a 12 tesla FTICR also allows precise label-free quantitation. Using two ion traps in parallel with one LC allows simultaneous MS/MS experiments and optimal application of collision induced dissociation and electron-transfer dissociation throughout the chromatographic separation for increased proteome coverage, characterization of post-translational modifications and/or simultaneous measurement in positive and negative ionization mode. An FTICR-ion trap cluster can achieve similar performance and sample throughput as multiple hybrid ion trap-FTICR instruments, but at a lower cost. We here describe the first such FTICR-ion trap cluster, its performance and the idea of chromatographic compression.